Figure 1 Extension of the Ulseth etal 2019 eD~k600 scaling model that is completely RS-able. This is how we are able to scale k600 using just SWOT observables.
Figure 2 Validation of five k600 upscaling models on 20% of the Ulseth etal 2019 dataset witheld for independent testing. Raymond Eq. 5 predicts negative k600 values, which are not plotted here and highlight the limitation of a linear model for this problem.
Figure 3 Model uncertainity estimates: a) histogram of SDs for all 8,000 MC simulations b) Three example MC simulations of 10,000 samples each c) Map of the 8,000 sets of hydraulic measurements used for this analysis
The average lnSD (i.e. k600 estimate uncertainity) is 1.31 (~3.7 m/dy).
Figure 4 Validation of remote sensing algorithm for 22 rivers with 11 day sampling intervals. Black bars are 95% CIs for the modeled values. Grey line is linear regression (and 95% predicition intervals) and dashed black line is 1:1 line.
Figure 5 a) Performance metrics by river. b)-d): validation timeseries for three rivers, where the model results include the posterior means and 95% CIs: b) randomly selected from upper tertile of kge scores c) randomly selected from middle tertile, d) randomly selected from worse tertile
kco2 was backed out using a Schmidt number for CO2 and 25C temp following Raymond etal 2012 and Wanninkof (1992)
air-side pCO2 was assumed to be 390 uatm
Figure 6 shows the resulting timeseries of FCO2 [\(g/m2*dy\)]). Basically, we reproduce scaling model dynamics and magntiude, but there is some scatter around this line. Basically, works in some rivers and not others. Need to parse this out.
Figure 6 Left: FCO2 from BIKER versus using observed average flow velocity for all timesteps for 22 SWOT rivers (grey lines are linear regression and 95% prediciton intervals, while black dashed line is the 1:1 line). right: timeseries plots for three example rivers.
Finally, we wanted to see how our completely ungauged, no in situ information algorithm compares against gauged approaches for estimating average flow velocity. We used two V~Q rating curves used for global CO2 upscaling efforts (Liu et al. in review; Raymond etal. 2013).
Figure 7 Left: barplots of total flux, per day and m2, of CO2 off of the 22 SWOT rivers for BIKER and threevelocity models: observed velocity and two hydraulic geomtery models (using observed discharge) used for global CO2 upscaling. Right: Cummulative density functions (CDFs) of all FCO2 estimates across all timesteps and rivers for the same set of velocity models.
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